{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "anomalies = pd.read_csv('anomaly_list.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_esb(anomaly):\n",
    "    esb = pd.read_csv(anomaly['folder'] + '/esb.csv')\n",
    "    return esb\n",
    "    \n",
    "def get_trace(anomaly):\n",
    "    trace = pd.read_csv(anomaly['folder'] + '/trace.csv')\n",
    "    return trace\n",
    "\n",
    "def get_host(anomaly):\n",
    "    host = pd.read_csv(anomaly['folder'] + '/host.csv')\n",
    "    return host"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### ESB and Host / KPI information for Faults"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "def print_fault_esb():\n",
    "    for fault in anomalies['fault'].unique():\n",
    "        print('*'*40)\n",
    "        print(fault)\n",
    "        for row_index in range(len(anomalies)):\n",
    "            anomaly = anomalies.iloc[row_index,:]\n",
    "            if anomaly['fault'] == fault:\n",
    "                print('-'*40)\n",
    "                print(anomaly['host'], anomaly['kpi'])\n",
    "                print(get_esb(anomalies.iloc[row_index,:]).tail())  \n",
    "                "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "****************************************\n",
      "CPU fault\n",
      "----------------------------------------\n",
      "docker_003 container_cpu_used\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "10     osb_001  1586534820000   17.0701    8           8       1.0000\n",
      "11     osb_001  1586534880000    5.0794  133         133       1.0000\n",
      "12     osb_001  1586534940000    3.9917   71          70       0.9859\n",
      "13     osb_001  1586534940000   72.6047   10           6       0.6000\n",
      "14     osb_001  1586535000000    1.2715  379         376       0.9921\n",
      "----------------------------------------\n",
      "docker_004 container_cpu_used\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "29     osb_001  1586540580000    4.1229  123         123       1.0000\n",
      "30     osb_001  1586540580000   15.1241    9           9       1.0000\n",
      "31     osb_001  1586540640000    7.2725  102          98       0.9608\n",
      "32     osb_001  1586540700000    1.3557  352         349       0.9915\n",
      "33     osb_001  1586540700000    1.5535    2           2       1.0000\n",
      "----------------------------------------\n",
      "docker_002 container_cpu_used\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "28     osb_001  1586544720000    5.5656  119         119       1.0000\n",
      "29     osb_001  1586544780000    4.2142  117         117       1.0000\n",
      "30     osb_001  1586544780000   21.3616    8           8       1.0000\n",
      "31     osb_001  1586544840000   11.2500   62          58       0.9355\n",
      "32     osb_001  1586544900000    3.0688   84          76       0.9048\n",
      "----------------------------------------\n",
      "docker_008 container_cpu_used\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "28     osb_001  1586551320000    1.8924  326         326          1.0\n",
      "29     osb_001  1586551380000    2.7164  198         198          1.0\n",
      "30     osb_001  1586551380000    8.9892   10          10          1.0\n",
      "31     osb_001  1586551440000    3.9719  167         167          1.0\n",
      "32     osb_001  1586551500000    0.6753  508         508          1.0\n",
      "----------------------------------------\n",
      "docker_001 container_cpu_used\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "32     osb_001  1590079860000    5.1641   94          94       1.0000\n",
      "33     osb_001  1590079860000   32.5080    9           9       1.0000\n",
      "34     osb_001  1590079920000    7.6282   89          86       0.9663\n",
      "35     osb_001  1590079980000    4.9066   96          96       1.0000\n",
      "36     osb_001  1590079980000   32.0986    9           9       1.0000\n",
      "----------------------------------------\n",
      "docker_005 container_cpu_used\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "43     osb_001  1590085260000    1.6953  336         336          1.0\n",
      "44     osb_001  1590085260000    4.2555    4           4          1.0\n",
      "45     osb_001  1590085320000    3.1154  189         189          1.0\n",
      "46     osb_001  1590085380000    2.7835  194         194          1.0\n",
      "47     osb_001  1590085380000    9.9418    9           9          1.0\n",
      "----------------------------------------\n",
      "docker_004 container_cpu_used\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "9      osb_001  1590163620000   17.5297    9           9         1.00\n",
      "10     osb_001  1590163680000    4.3636  145         145         1.00\n",
      "11     osb_001  1590163740000    4.9627   80          80         1.00\n",
      "12     osb_001  1590163740000   68.0958   10           6         0.60\n",
      "13     osb_001  1590163800000    1.1519  250         240         0.96\n",
      "----------------------------------------\n",
      "docker_006 container_cpu_used\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "29     osb_001  1590180540000    6.4900   10          10          1.0\n",
      "30     osb_001  1590180600000    3.5173  176         176          1.0\n",
      "31     osb_001  1590180660000    2.9968  180         180          1.0\n",
      "32     osb_001  1590180660000   12.4498   10          10          1.0\n",
      "33     osb_001  1590180720000    0.8679  497         497          1.0\n",
      "----------------------------------------\n",
      "docker_003 container_cpu_used\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "29     osb_001  1590261540000   14.8023   10          10          1.0\n",
      "30     osb_001  1590261600000    4.8191  136         136          1.0\n",
      "31     osb_001  1590261660000    2.8814  104         104          1.0\n",
      "32     osb_001  1590261660000   50.5765   10          10          1.0\n",
      "33     osb_001  1590261720000    1.7971  311         311          1.0\n",
      "----------------------------------------\n",
      "docker_006 container_cpu_used\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "29     osb_001  1590265140000    8.5320    9           9          1.0\n",
      "30     osb_001  1590265200000    3.1857  195         195          1.0\n",
      "31     osb_001  1590265260000    3.0956  170         170          1.0\n",
      "32     osb_001  1590265260000   12.7612    9           9          1.0\n",
      "33     osb_001  1590265320000    0.9044  460         460          1.0\n",
      "----------------------------------------\n",
      "docker_008 container_cpu_used\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "28     osb_001  1590432060000    4.9808   10          10       1.0000\n",
      "29     osb_001  1590432120000    2.6441  241         241       1.0000\n",
      "30     osb_001  1590432180000    4.2919  128         128       1.0000\n",
      "31     osb_001  1590432180000    9.9334    7           7       1.0000\n",
      "32     osb_001  1590432240000    3.0861  188         187       0.9947\n",
      "----------------------------------------\n",
      "docker_002 container_cpu_used\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "29     osb_001  1590441420000   16.4666    9           9          1.0\n",
      "30     osb_001  1590441480000    4.7261  141         141          1.0\n",
      "31     osb_001  1590441540000    3.8158   98          98          1.0\n",
      "32     osb_001  1590441540000   39.8300   10          10          1.0\n",
      "33     osb_001  1590441600000    3.6678  159         159          1.0\n",
      "----------------------------------------\n",
      "docker_006 container_cpu_used\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "28     osb_001  1590513900000    5.0316    9           9          1.0\n",
      "29     osb_001  1590513960000    2.1696  277         277          1.0\n",
      "30     osb_001  1590514020000    2.7051  196         196          1.0\n",
      "31     osb_001  1590514020000    9.9501    9           9          1.0\n",
      "32     osb_001  1590514080000    3.5361  171         171          1.0\n",
      "----------------------------------------\n",
      "docker_001 container_cpu_used\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "29     osb_001  1590527460000   15.9406    8           8          1.0\n",
      "30     osb_001  1590527520000    5.8441  114         114          1.0\n",
      "31     osb_001  1590527580000    4.1088  124         124          1.0\n",
      "32     osb_001  1590527580000   23.1796    8           8          1.0\n",
      "33     osb_001  1590527640000    1.9065  307         307          1.0\n",
      "----------------------------------------\n",
      "docker_001 container_cpu_used\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "30     osb_001  1590598200000    6.1650   92          92       1.0000\n",
      "31     osb_001  1590598200000   85.5439    7           7       1.0000\n",
      "32     osb_001  1590598260000    0.3930  101          99       0.9802\n",
      "33     osb_001  1590598260000   88.6484    8           8       1.0000\n",
      "34     osb_001  1590598320000    0.9800  507         505       0.9961\n",
      "----------------------------------------\n",
      "docker_008 container_cpu_used\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "43     osb_001  1590691440000    2.8949  214         214          1.0\n",
      "44     osb_001  1590691500000    3.2625  170         170          1.0\n",
      "45     osb_001  1590691500000    9.2233    6           6          1.0\n",
      "46     osb_001  1590691560000    2.3130  232         232          1.0\n",
      "47     osb_001  1590691560000    0.0000    1           0          0.0\n",
      "----------------------------------------\n",
      "docker_001 container_cpu_used\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "52     osb_001  1590694980000   26.1386    7           7          1.0\n",
      "53     osb_001  1590695040000    5.9842  111         111          1.0\n",
      "54     osb_001  1590695100000    5.9364   87          87          1.0\n",
      "55     osb_001  1590695100000   19.1540    8           8          1.0\n",
      "56     osb_001  1590695160000    6.7862   89          89          1.0\n",
      "----------------------------------------\n",
      "docker_002 container_cpu_used\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "28     osb_001  1590783300000   19.7617    8           8       1.0000\n",
      "29     osb_001  1590783360000    6.4633  125         125       1.0000\n",
      "30     osb_001  1590783420000    6.4224   73          72       0.9863\n",
      "31     osb_001  1590783420000   25.4081   10          10       1.0000\n",
      "32     osb_001  1590783480000    8.4529   81          81       1.0000\n",
      "----------------------------------------\n",
      "docker_004 container_cpu_used\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "28     osb_001  1590869940000   16.2482    8           8        1.000\n",
      "29     osb_001  1590870000000    4.4989  147         147        1.000\n",
      "30     osb_001  1590870060000    4.4929   95          95        1.000\n",
      "31     osb_001  1590870060000   79.9072   10           6        0.600\n",
      "32     osb_001  1590870120000    0.5454   32          20        0.625\n",
      "****************************************\n",
      "network delay\n",
      "----------------------------------------\n",
      "docker_002 nan\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "26     osb_001  1586536560000    1.2353  479         479          1.0\n",
      "27     osb_001  1586536620000    1.0870  472         472          1.0\n",
      "28     osb_001  1586536680000    1.1959  464         464          1.0\n",
      "29     osb_001  1586536740000    1.0722  498         498          1.0\n",
      "30     osb_001  1586536800000    0.4864  534         534          1.0\n",
      "----------------------------------------\n",
      "docker_001 nan\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "28     osb_001  1586538720000    1.2317  477         477          1.0\n",
      "29     osb_001  1586538780000    1.1500  494         494          1.0\n",
      "30     osb_001  1586538780000    4.1750    5           5          1.0\n",
      "31     osb_001  1586538840000    1.1799  497         497          1.0\n",
      "32     osb_001  1586538900000    0.5492  557         557          1.0\n",
      "----------------------------------------\n",
      "docker_003 nan\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "27     osb_001  1586546460000    7.5720    1           1          1.0\n",
      "28     osb_001  1586546520000    1.1065  417         417          1.0\n",
      "29     osb_001  1586546580000    1.1089  400         400          1.0\n",
      "30     osb_001  1586546640000    1.0322  440         440          1.0\n",
      "31     osb_001  1586546700000    0.5280  445         445          1.0\n",
      "----------------------------------------\n",
      "docker_005 nan\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "34     osb_001  1590081660000    3.8408  127         127          1.0\n",
      "35     osb_001  1590081660000   12.4850    8           8          1.0\n",
      "36     osb_001  1590081660000    0.0000    1           0          0.0\n",
      "37     osb_001  1590081720000    4.5124  139         139          1.0\n",
      "38     osb_001  1590081780000    3.4007  171         171          1.0\n",
      "----------------------------------------\n",
      "os_018 Sent_queue;Received_queue\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "39     osb_001  1590083460000    8.2772   35          35          1.0\n",
      "40     osb_001  1590083460000   44.9690   10          10          1.0\n",
      "41     osb_001  1590083520000   16.2477   48          48          1.0\n",
      "42     osb_001  1590083580000    6.3264   92          92          1.0\n",
      "43     osb_001  1590083580000    1.6980    2           2          1.0\n",
      "----------------------------------------\n",
      "docker_007 nan\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "34     osb_001  1590096060000    3.5540  154         154          1.0\n",
      "35     osb_001  1590096060000    9.1467    9           9          1.0\n",
      "36     osb_001  1590096120000    4.6099  146         146          1.0\n",
      "37     osb_001  1590096180000    3.8671  149         149          1.0\n",
      "38     osb_001  1590096180000    1.5885    4           4          1.0\n",
      "----------------------------------------\n",
      "docker_006 nan\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "33     osb_001  1590097860000    3.7588  146         146          1.0\n",
      "34     osb_001  1590097860000   10.4805    6           6          1.0\n",
      "35     osb_001  1590097920000    3.8694  167         167          1.0\n",
      "36     osb_001  1590097980000    3.2378  178         178          1.0\n",
      "37     osb_001  1590097980000    6.4170    1           1          1.0\n",
      "----------------------------------------\n",
      "docker_006 nan\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "28     osb_001  1590174120000    6.1511  110         110          1.0\n",
      "29     osb_001  1590174180000    5.3127   98          98          1.0\n",
      "30     osb_001  1590174180000   11.0812    6           6          1.0\n",
      "31     osb_001  1590174240000    6.0248  105         105          1.0\n",
      "32     osb_001  1590174300000    0.7281  428         428          1.0\n",
      "----------------------------------------\n",
      "os_021 Sent_queue;Received_queue\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "28     osb_001  1590176280000    8.2241   60          60          1.0\n",
      "29     osb_001  1590176340000    6.0731   54          54          1.0\n",
      "30     osb_001  1590176340000   16.3469   10          10          1.0\n",
      "31     osb_001  1590176400000    8.1302   57          57          1.0\n",
      "32     osb_001  1590176460000    0.6126  358         358          1.0\n",
      "----------------------------------------\n",
      "docker_005 nan\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "28     osb_001  1590182520000    6.9154  103         103          1.0\n",
      "29     osb_001  1590182580000    4.5580  105         105          1.0\n",
      "30     osb_001  1590182580000   16.3720   10          10          1.0\n",
      "31     osb_001  1590182640000    5.7630  110         110          1.0\n",
      "32     osb_001  1590182700000    0.7190  561         561          1.0\n",
      "----------------------------------------\n",
      "docker_004 nan\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "29     osb_001  1590266940000    4.3728    6           6          1.0\n",
      "30     osb_001  1590267000000    1.1973  486         486          1.0\n",
      "31     osb_001  1590267060000    1.3139  420         420          1.0\n",
      "32     osb_001  1590267060000    5.1680    8           8          1.0\n",
      "33     osb_001  1590267120000    0.5539  499         499          1.0\n",
      "----------------------------------------\n",
      "os_020 Sent_queue;Received_queue\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "31     osb_001  1590342600000   14.0562   30          23       0.7667\n",
      "32     osb_001  1590342600000   89.5637    6           6       1.0000\n",
      "33     osb_001  1590342660000    6.5109   24          16       0.6667\n",
      "34     osb_001  1590342660000   36.2295   10          10       1.0000\n",
      "35     osb_001  1590342720000    0.7545  404         404       1.0000\n",
      "----------------------------------------\n",
      "os_021 Sent_queue;Received_queue\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "28     osb_001  1590433860000   15.6201   10          10        1.000\n",
      "29     osb_001  1590433920000    9.4879   52          52        1.000\n",
      "30     osb_001  1590433980000    6.5051   49          49        1.000\n",
      "31     osb_001  1590433980000   15.2761   10          10        1.000\n",
      "32     osb_001  1590434040000    1.7498  247         246        0.996\n",
      "----------------------------------------\n",
      "os_020 Sent_queue;Received_queue\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "31     osb_001  1590437880000   12.6834   20          14       0.7000\n",
      "32     osb_001  1590437880000  121.1616    8           8       1.0000\n",
      "33     osb_001  1590437940000   10.5909   21          13       0.6190\n",
      "34     osb_001  1590437940000   53.2258   10           9       0.9000\n",
      "35     osb_001  1590438000000    0.6869  465         462       0.9935\n",
      "----------------------------------------\n",
      "os_001 Sent_queue;Received_queue\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "29     osb_001  1590439620000   22.5411   10          10          1.0\n",
      "30     osb_001  1590439680000   24.3751   30          30          1.0\n",
      "31     osb_001  1590439740000   24.3071   20          20          1.0\n",
      "32     osb_001  1590439740000   20.6895   10          10          1.0\n",
      "33     osb_001  1590439800000    0.8911  522         522          1.0\n",
      "----------------------------------------\n",
      "os_018 Sent_queue;Received_queue\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "26     osb_001  1590510300000   27.7862   10          10          1.0\n",
      "27     osb_001  1590510360000   17.6681   40          40          1.0\n",
      "28     osb_001  1590510420000   10.4294   36          36          1.0\n",
      "29     osb_001  1590510420000   34.3955   10          10          1.0\n",
      "30     osb_001  1590510480000    2.1447  271         271          1.0\n",
      "----------------------------------------\n",
      "os_017 Sent_queue;Received_queue\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "28     osb_001  1590512100000   33.7957   10          10          1.0\n",
      "29     osb_001  1590512160000   10.3752   66          66          1.0\n",
      "30     osb_001  1590512220000    7.7585   58          58          1.0\n",
      "31     osb_001  1590512220000   24.7946    9           9          1.0\n",
      "32     osb_001  1590512280000    1.9751  294         294          1.0\n",
      "----------------------------------------\n",
      "docker_001 nan\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "28     osb_001  1590521100000   11.6272    5           5          1.0\n",
      "29     osb_001  1590521160000    2.3351  261         261          1.0\n",
      "30     osb_001  1590521220000    2.5241  205         205          1.0\n",
      "31     osb_001  1590521220000   13.3736   10          10          1.0\n",
      "32     osb_001  1590521280000    1.6101  360         360          1.0\n",
      "----------------------------------------\n",
      "os_021 Sent_queue;Received_queue\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "29     osb_001  1590529260000    6.4215    8           8          1.0\n",
      "30     osb_001  1590529320000    2.8693  160         160          1.0\n",
      "31     osb_001  1590529380000    2.8255  146         146          1.0\n",
      "32     osb_001  1590529380000    6.1190    9           9          1.0\n",
      "33     osb_001  1590529440000    0.6958  589         589          1.0\n",
      "----------------------------------------\n",
      "docker_001 nan\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "29     osb_001  1590599940000    4.7492    4           4          1.0\n",
      "30     osb_001  1590600000000    1.2418  468         468          1.0\n",
      "31     osb_001  1590600060000    1.1647  452         452          1.0\n",
      "32     osb_001  1590600060000    4.4593    3           3          1.0\n",
      "33     osb_001  1590600120000    0.5915  602         602          1.0\n",
      "----------------------------------------\n",
      "docker_001 nan\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "26     osb_001  1590607080000    1.1879  414         414          1.0\n",
      "27     osb_001  1590607140000    1.2540  410         410          1.0\n",
      "28     osb_001  1590607200000    1.1259  402         402          1.0\n",
      "29     osb_001  1590607260000    1.1525  442         442          1.0\n",
      "30     osb_001  1590607320000    0.5357  418         418          1.0\n",
      "----------------------------------------\n",
      "docker_006 nan\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "52     osb_001  1590700380000   19.4012   10          10          1.0\n",
      "53     osb_001  1590700440000   10.6335   68          68          1.0\n",
      "54     osb_001  1590700500000   10.8431   47          47          1.0\n",
      "55     osb_001  1590700500000   22.9430   10          10          1.0\n",
      "56     osb_001  1590700560000    3.1562  194         194          1.0\n",
      "----------------------------------------\n",
      "os_009 Sent_queue;Received_queue\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "28     osb_001  1590777900000    0.0000    9           0       0.0000\n",
      "29     osb_001  1590777960000    6.1720   31           1       0.0323\n",
      "30     osb_001  1590778020000   16.3150   20           1       0.0500\n",
      "31     osb_001  1590778020000    0.0000   10           0       0.0000\n",
      "32     osb_001  1590778080000    1.0815  366         357       0.9754\n",
      "----------------------------------------\n",
      "os_020 Sent_queue;Received_queue\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "30     osb_001  1590781560000   16.6729   26          16       0.6154\n",
      "31     osb_001  1590781560000  122.5694    7           7       1.0000\n",
      "32     osb_001  1590781620000    2.7348   26          13       0.5000\n",
      "33     osb_001  1590781620000   69.6875   10          10       1.0000\n",
      "34     osb_001  1590781680000    1.3161  329         321       0.9757\n",
      "----------------------------------------\n",
      "docker_002 nan\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "27     osb_001  1590788700000    1.2078  460         460          1.0\n",
      "28     osb_001  1590788700000    4.4107    7           7          1.0\n",
      "29     osb_001  1590788760000    1.1123  515         515          1.0\n",
      "30     osb_001  1590788820000    1.1994  468         468          1.0\n",
      "31     osb_001  1590788880000    0.9354  585         585          1.0\n",
      "----------------------------------------\n",
      "docker_007 nan\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "20     osb_001  1590855540000   23.9048   10          10          1.0\n",
      "21     osb_001  1590855600000    7.2297   90          90          1.0\n",
      "22     osb_001  1590855660000    4.8676  112         112          1.0\n",
      "23     osb_001  1590855660000   11.0453    9           9          1.0\n",
      "24     osb_001  1590855720000    1.2136  452         452          1.0\n",
      "----------------------------------------\n",
      "docker_001 nan\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "28     osb_001  1590857340000    6.3688    4           4          1.0\n",
      "29     osb_001  1590857400000    1.1584  505         505          1.0\n",
      "30     osb_001  1590857460000    1.1207  506         506          1.0\n",
      "31     osb_001  1590857460000    5.0497    6           6          1.0\n",
      "32     osb_001  1590857520000    0.7839  516         516          1.0\n",
      "----------------------------------------\n",
      "docker_008 nan\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "28     osb_001  1590862740000   12.9073    9           9          1.0\n",
      "29     osb_001  1590862800000    5.3367  119         119          1.0\n",
      "30     osb_001  1590862860000    4.4646  117         117          1.0\n",
      "31     osb_001  1590862860000   13.6974    8           8          1.0\n",
      "32     osb_001  1590862920000    1.0712  517         517          1.0\n",
      "----------------------------------------\n",
      "os_021 Sent_queue;Received_queue\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "28     osb_001  1590864540000   16.5292   10          10          1.0\n",
      "29     osb_001  1590864600000    8.4350   57          57          1.0\n",
      "30     osb_001  1590864660000    6.3638   50          50          1.0\n",
      "31     osb_001  1590864660000   15.0048   10          10          1.0\n",
      "32     osb_001  1590864720000    1.0028  440         440          1.0\n",
      "----------------------------------------\n",
      "os_017 Sent_queue;Received_queue\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "29     osb_001  1590866400000   24.7179   29          22       0.7586\n",
      "30     osb_001  1590866400000  105.7445    2           2       1.0000\n",
      "31     osb_001  1590866460000    4.3571   21           9       0.4286\n",
      "32     osb_001  1590866460000   68.3408   10          10       1.0000\n",
      "33     osb_001  1590866520000    0.9965  406         396       0.9754\n",
      "----------------------------------------\n",
      "docker_006 nan\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "28     osb_001  1590871740000   18.2298    9           9          1.0\n",
      "29     osb_001  1590871800000    8.3217   89          89          1.0\n",
      "30     osb_001  1590871860000    5.6150   92          92          1.0\n",
      "31     osb_001  1590871860000   14.7336   10          10          1.0\n",
      "32     osb_001  1590871920000    1.1259  497         497          1.0\n",
      "****************************************\n",
      "db connection limit\n",
      "----------------------------------------\n",
      "db_007 Proc_User_Used_Pct;Proc_Used_Pct;Sess_Connect\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "26     osb_001  1586542560000    0.0000  541           0       0.0000\n",
      "27     osb_001  1586542620000    0.0000  586           0       0.0000\n",
      "28     osb_001  1586542680000    0.0000  580           0       0.0000\n",
      "29     osb_001  1586542740000    0.0000  541           0       0.0000\n",
      "30     osb_001  1586542800000    0.5817  529         519       0.9811\n",
      "----------------------------------------\n",
      "db_003 Proc_User_Used_Pct;Proc_Used_Pct;Sess_Connect\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "26     osb_001  1590165660000    0.0000  514           0        0.000\n",
      "27     osb_001  1590165720000    0.0000  500           0        0.000\n",
      "28     osb_001  1590165780000    0.0000  496           0        0.000\n",
      "29     osb_001  1590165840000    0.0000  512           0        0.000\n",
      "30     osb_001  1590165900000    0.6164  512         490        0.957\n",
      "----------------------------------------\n",
      "db_007 Proc_User_Used_Pct;Proc_Used_Pct;Sess_Connect\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "26     osb_001  1590430200000    0.6150  547         535       0.9781\n",
      "27     osb_001  1590430260000    0.6085  576         576       1.0000\n",
      "28     osb_001  1590430320000    0.6021  459         459       1.0000\n",
      "29     osb_001  1590430380000    0.5910  569         569       1.0000\n",
      "30     osb_001  1590430440000    0.6437  520         520       1.0000\n",
      "----------------------------------------\n",
      "db_003 Proc_User_Used_Pct;Proc_Used_Pct;Sess_Connect\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "26     osb_001  1590515640000    0.5291  539         515       0.9555\n",
      "27     osb_001  1590515700000    0.5597  542         542       1.0000\n",
      "28     osb_001  1590515760000    0.5406  536         536       1.0000\n",
      "29     osb_001  1590515820000    0.5003  525         525       1.0000\n",
      "30     osb_001  1590515880000    0.4985  512         512       1.0000\n",
      "----------------------------------------\n",
      "db_007 Proc_User_Used_Pct;Proc_Used_Pct;Sess_Connect\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "26     osb_001  1590519240000    0.4744  418         407       0.9737\n",
      "27     osb_001  1590519300000    0.4717  409         409       1.0000\n",
      "28     osb_001  1590519360000    0.4477  395         395       1.0000\n",
      "29     osb_001  1590519420000    0.5137  399         399       1.0000\n",
      "30     osb_001  1590519480000    0.4425  425         425       1.0000\n",
      "----------------------------------------\n",
      "db_003 Proc_User_Used_Pct;Proc_Used_Pct;Sess_Connect\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "44     osb_001  1590689640000    1.6732  370         370          1.0\n",
      "45     osb_001  1590689700000    1.1117  470         470          1.0\n",
      "46     osb_001  1590689700000    7.4165    2           2          1.0\n",
      "47     osb_001  1590689760000    1.4060  396         396          1.0\n",
      "48     osb_001  1590689760000    0.0000    1           0          0.0\n",
      "----------------------------------------\n",
      "db_003 Proc_User_Used_Pct;Proc_Used_Pct;Sess_Connect\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "26     osb_001  1590868080000       0.0  413           0          0.0\n",
      "27     osb_001  1590868140000       0.0  454           0          0.0\n",
      "28     osb_001  1590868200000       0.0  426           0          0.0\n",
      "29     osb_001  1590868260000       0.0  422           0          0.0\n",
      "30     osb_001  1590868320000       0.0  453           0          0.0\n",
      "****************************************\n",
      "network loss\n",
      "----------------------------------------\n",
      "docker_003 nan\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "29     osb_001  1586548620000   47.1170    2           2          1.0\n",
      "30     osb_001  1586548680000    0.8491  410         410          1.0\n",
      "31     osb_001  1586548740000    0.7924  425         425          1.0\n",
      "32     osb_001  1586548740000   62.0950    1           1          1.0\n",
      "33     osb_001  1586548800000    0.5588  433         433          1.0\n",
      "----------------------------------------\n",
      "docker_007 nan\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "31     osb_001  1586552820000    0.0000    9           0       0.0000\n",
      "32     osb_001  1586552880000    1.9993  259         207       0.7992\n",
      "33     osb_001  1586552940000    1.2546  348         348       1.0000\n",
      "34     osb_001  1586552940000   20.8780   10          10       1.0000\n",
      "35     osb_001  1586553000000    0.6161  545         545       1.0000\n",
      "----------------------------------------\n",
      "os_021 Sent_queue;Received_queue\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "29     osb_001  1590167880000   85.4370    1           1       1.0000\n",
      "30     osb_001  1590167940000    3.6185   81          79       0.9753\n",
      "31     osb_001  1590167940000   58.6467    6           3       0.5000\n",
      "32     osb_001  1590168000000    4.6901   92          90       0.9783\n",
      "33     osb_001  1590168060000    0.6066  594         594       1.0000\n",
      "----------------------------------------\n",
      "os_009 Sent_queue;Received_queue\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "28     osb_001  1590170040000    0.9295  605         605       1.0000\n",
      "29     osb_001  1590170100000    0.9329  563         563       1.0000\n",
      "30     osb_001  1590170100000    7.6050    1           1       1.0000\n",
      "31     osb_001  1590170160000    1.0386  538         537       0.9981\n",
      "32     osb_001  1590170220000    0.5446  592         592       1.0000\n",
      "----------------------------------------\n",
      "docker_007 nan\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "28     osb_001  1590184620000    1.6073  350         350          1.0\n",
      "29     osb_001  1590184620000    3.5240    7           7          1.0\n",
      "30     osb_001  1590184680000    2.0400  317         317          1.0\n",
      "31     osb_001  1590184740000    2.2327  253         253          1.0\n",
      "32     osb_001  1590184740000    4.2570    1           1          1.0\n",
      "----------------------------------------\n",
      "docker_004 nan\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "19     osb_001  1590250680000    0.6242  462         462          1.0\n",
      "20     osb_001  1590250740000    0.7596  499         499          1.0\n",
      "21     osb_001  1590250800000    0.6891  408         408          1.0\n",
      "22     osb_001  1590250860000    0.6633  492         492          1.0\n",
      "23     osb_001  1590250920000    0.4645  461         461          1.0\n",
      "----------------------------------------\n",
      "docker_002 nan\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "27     osb_001  1590259740000    0.7755  449         449          1.0\n",
      "28     osb_001  1590259800000    0.7426  450         450          1.0\n",
      "29     osb_001  1590259860000    0.9636  466         466          1.0\n",
      "30     osb_001  1590259860000   26.4590    1           1          1.0\n",
      "31     osb_001  1590259920000    0.5595  449         449          1.0\n",
      "----------------------------------------\n",
      "os_017 Sent_queue;Received_queue\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "29     osb_001  1590349740000    8.0024    8           8        1.000\n",
      "30     osb_001  1590349800000    3.2551  197         197        1.000\n",
      "31     osb_001  1590349860000    2.4557  214         211        0.986\n",
      "32     osb_001  1590349860000    5.6227    8           8        1.000\n",
      "33     osb_001  1590349920000    0.5557  445         445        1.000\n",
      "----------------------------------------\n",
      "docker_003 nan\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "26     osb_001  1590424380000    0.7342  457         457          1.0\n",
      "27     osb_001  1590424440000    0.8691  461         461          1.0\n",
      "28     osb_001  1590424500000    0.6706  431         431          1.0\n",
      "29     osb_001  1590424560000    0.7518  516         516          1.0\n",
      "30     osb_001  1590424620000    0.6752  475         475          1.0\n",
      "----------------------------------------\n",
      "os_018 Sent_queue;Received_queue\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "29     osb_001  1590435660000   59.8235   10          10          1.0\n",
      "30     osb_001  1590435720000    2.6109  242         242          1.0\n",
      "31     osb_001  1590435780000    2.3944  242         242          1.0\n",
      "32     osb_001  1590435780000    6.7092    6           6          1.0\n",
      "33     osb_001  1590435840000    1.4125  397         397          1.0\n",
      "----------------------------------------\n",
      "docker_007 nan\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "31     osb_001  1590525720000   11.5870   54          50       0.9259\n",
      "32     osb_001  1590525720000  118.0820    2           1       0.5000\n",
      "33     osb_001  1590525780000    7.2086   18          17       0.9444\n",
      "34     osb_001  1590525780000   66.2892   12          11       0.9167\n",
      "35     osb_001  1590525840000    0.7616  517         503       0.9729\n",
      "----------------------------------------\n",
      "os_018 Sent_queue;Received_queue\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "31     osb_001  1590609000000    3.8457  149         147       0.9866\n",
      "32     osb_001  1590609000000  131.8780    1           1       1.0000\n",
      "33     osb_001  1590609060000    2.9125  181         181       1.0000\n",
      "34     osb_001  1590609060000    8.3274    9           9       1.0000\n",
      "35     osb_001  1590609120000    0.6119  444         444       1.0000\n",
      "----------------------------------------\n",
      "docker_008 nan\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "29     osb_001  1590614340000    4.1217    3           3          1.0\n",
      "30     osb_001  1590614400000    1.7895  327         327          1.0\n",
      "31     osb_001  1590614460000    1.2491  455         455          1.0\n",
      "32     osb_001  1590614460000    3.7740    5           5          1.0\n",
      "33     osb_001  1590614520000    0.5715  596         596          1.0\n",
      "----------------------------------------\n",
      "os_021 Sent_queue;Received_queue\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "17     osb_001  1590768900000   11.9650    7           5       0.7143\n",
      "18     osb_001  1590768960000    2.3884  169         168       0.9941\n",
      "19     osb_001  1590769020000    1.9938  151         147       0.9735\n",
      "20     osb_001  1590769020000    2.7540    4           4       1.0000\n",
      "21     osb_001  1590769080000    1.0033  426         426       1.0000\n",
      "----------------------------------------\n",
      "docker_005 nan\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "27     osb_001  1590770700000    1.2044  464         464       1.0000\n",
      "28     osb_001  1590770700000    5.2923    6           6       1.0000\n",
      "29     osb_001  1590770760000    3.4552  180         179       0.9944\n",
      "30     osb_001  1590770820000    1.3207  424         424       1.0000\n",
      "31     osb_001  1590770880000    1.0033  491         491       1.0000\n",
      "----------------------------------------\n",
      "docker_001 nan\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "28     osb_001  1590776100000   64.1420    2           2          1.0\n",
      "29     osb_001  1590776160000    1.1019  522         522          1.0\n",
      "30     osb_001  1590776220000    0.6997  583         583          1.0\n",
      "31     osb_001  1590776220000    0.0000    1           0          0.0\n",
      "32     osb_001  1590776280000    0.8164  580         580          1.0\n",
      "----------------------------------------\n",
      "os_018 Sent_queue;Received_queue\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "28     osb_001  1590786900000   13.2192    7           6       0.8571\n",
      "29     osb_001  1590786960000    4.3281  145         145       1.0000\n",
      "30     osb_001  1590787020000    2.9416  191         190       0.9948\n",
      "31     osb_001  1590787020000    5.1817    9           9       1.0000\n",
      "32     osb_001  1590787080000    1.1015  499         498       0.9980\n",
      "----------------------------------------\n",
      "docker_008 nan\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "28     osb_001  1590860940000   13.7990    1           1          1.0\n",
      "29     osb_001  1590861000000    3.4631  227         227          1.0\n",
      "30     osb_001  1590861060000    2.1030  276         276          1.0\n",
      "31     osb_001  1590861060000    3.8247    3           3          1.0\n",
      "32     osb_001  1590861120000    1.1319  396         396          1.0\n",
      "----------------------------------------\n",
      "docker_003 nan\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "27     osb_001  1590875400000    0.5071  594         594          1.0\n",
      "28     osb_001  1590875460000    0.5558  608         608          1.0\n",
      "29     osb_001  1590875460000  104.9130    1           1          1.0\n",
      "30     osb_001  1590875520000    0.4894  517         517          1.0\n",
      "31     osb_001  1590875580000    0.5876  539         539          1.0\n",
      "****************************************\n",
      "db  close\n",
      "----------------------------------------\n",
      "db_003 On_Off_State;tnsping_result_time\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "26     osb_001  1586555160000    0.0000  565           0       0.0000\n",
      "27     osb_001  1586555220000    0.0000  472           0       0.0000\n",
      "28     osb_001  1586555280000    0.0000  652           0       0.0000\n",
      "29     osb_001  1586555340000    0.0000  585           0       0.0000\n",
      "30     osb_001  1586555400000    0.5527  594         267       0.4495\n",
      "----------------------------------------\n",
      "db_003 On_Off_State;tnsping_result_time\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "8      osb_001  1590077280000    0.0000  355           0       0.0000\n",
      "9      osb_001  1590077340000    0.0000  359           0       0.0000\n",
      "10     osb_001  1590077400000    0.0000  388           0       0.0000\n",
      "11     osb_001  1590077460000    0.0000  385           0       0.0000\n",
      "12     osb_001  1590077520000    1.1762  421         203       0.4822\n",
      "----------------------------------------\n",
      "db_007 On_Off_State;tnsping_result_time\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "26     osb_001  1590256080000    0.0000  576           0       0.0000\n",
      "27     osb_001  1590256140000    0.0000  599           0       0.0000\n",
      "28     osb_001  1590256200000    0.0000  570           0       0.0000\n",
      "29     osb_001  1590256260000    0.0000  498           0       0.0000\n",
      "30     osb_001  1590256320000    0.6413  399         362       0.9073\n",
      "----------------------------------------\n",
      "db_003 On_Off_State;tnsping_result_time\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "26     osb_001  1590353280000    0.9647  577         292       0.5061\n",
      "27     osb_001  1590353340000    0.9233  543         268       0.4936\n",
      "28     osb_001  1590353400000    0.9571  548         275       0.5018\n",
      "29     osb_001  1590353460000    0.9797  554         275       0.4964\n",
      "30     osb_001  1590353520000    0.6302  507         483       0.9527\n",
      "----------------------------------------\n",
      "db_007 On_Off_State;tnsping_result_time\n",
      "   serviceName      startTime  avg_time  num  succee_num  succee_rate\n",
      "26     osb_001  1590517440000       0.0  571           0          0.0\n",
      "27     osb_001  1590517500000       0.0  472           0          0.0\n",
      "28     osb_001  1590517560000       0.0  491           0          0.0\n",
      "29     osb_001  1590517620000       0.0  448           0          0.0\n",
      "30     osb_001  1590517680000       0.0  519           0          0.0\n"
     ]
    }
   ],
   "source": [
    "print_fault_esb()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "General Findings:\n",
    "- No discriminatory information in esb on fault types\n",
    "- Thresholds on avg_time and succee_rate will caputer all anomalies\n",
    "\n",
    "CPU Fault's:\n",
    "- Always in docker host's and container_cpu_used\n",
    "\n",
    "Network Delay:\n",
    "- Always in docker or os\n",
    "- Docker fault's have no kpi's\n",
    "- Os faults are always Sent_queue and Received_queue\n",
    "\n",
    "Network Loss:\n",
    "- Either in docker or os\n",
    "- If in docker no kpi's\n",
    "- If in os Sent_queue;Received_queue\n",
    "\n",
    "DB Connection Limit:\n",
    "- Always in db\n",
    "- Always with Proc_User_Used_Pct;Proc_Used_Pct;Sess_Connect\n",
    "\n",
    "DF Close:\n",
    "- Always in db\n",
    "- Always with On_Off_State;tnsping_result_time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_rel_kpi(anomaly):\n",
    "    kpi = get_host(anomaly)\n",
    "    if anomaly.fault == 'CPU fault':\n",
    "        kpi = kpi[(kpi.name == 'container_cpu_used')]\n",
    "    elif anomaly.fault == 'db connection limit':\n",
    "        kpi = kpi[(kpi.name == 'Proc_User_Used_Pct') or (kpi.name == '')]\n",
    "    return kpi\n",
    "\n",
    "def plot_rel_kpis(anomaly):\n",
    "    kpi = get_host(anomaly)\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "         timestamp  value\n",
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      "351  1586534642000    2.0\n",
      "352  1586534582000    1.0\n",
      "353  1586534548000    2.0\n",
      "354  1586534488000    2.0\n",
      "520  1586534961000   98.0\n",
      "521  1586534886000   98.0\n",
      "522  1586534787000    1.0\n",
      "          timestamp  value\n",
      "587   1586539346000    1.0\n",
      "588   1586539286000   10.0\n",
      "794   1586539824000    2.0\n",
      "795   1586539764000    2.0\n",
      "796   1586539704000    2.0\n",
      "797   1586539644000    1.0\n",
      "798   1586539562000    2.0\n",
      "1154  1586540126000    2.0\n",
      "1155  1586540042000    1.0\n",
      "1156  1586540005000    2.0\n",
      "1157  1586539946000    1.0\n",
      "1158  1586539885000    1.0\n",
      "1794  1586540426000    1.0\n",
      "1795  1586540366000    1.0\n",
      "1796  1586540305000    1.0\n",
      "1797  1586540246000    1.0\n",
      "1798  1586540185000    1.0\n",
      "1888  1586540645000  101.0\n",
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      "1890  1586540485000    2.0\n",
      "          timestamp  value\n",
      "468   1586543556000    2.0\n",
      "469   1586543497000    2.0\n",
      "920   1586544035000    2.0\n",
      "921   1586543976000    1.0\n",
      "922   1586543883000    2.0\n",
      "923   1586543856000    1.0\n",
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      "1461  1586544243000    2.0\n",
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      "          timestamp  value\n",
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      "1568  1590691326000    9.0\n",
      "1631  1590691388000   11.0\n",
      "1721  1590691459000   58.0\n",
      "          timestamp  value\n",
      "18    1590693545000   27.0\n",
      "108   1590693627000    3.0\n",
      "171   1590693686000   12.0\n",
      "239   1590693746000   15.0\n",
      "293   1590693806000   45.0\n",
      "419   1590693926000    3.0\n",
      "470   1590693986000    2.0\n",
      "533   1590694046000    8.0\n",
      "605   1590694106000    8.0\n",
      "668   1590694168000    4.0\n",
      "731   1590694226000   13.0\n",
      "798   1590694286000    2.0\n",
      "852   1590694346000    3.0\n",
      "888   1590694382000   12.0\n",
      "1029  1590694797000    3.0\n",
      "1083  1590694832000   23.0\n",
      "1143  1590694888000   61.0\n",
      "1161  1590694922000   32.0\n",
      "1269  1590695007000   24.0\n",
      "1377  1590695121000   82.0\n",
      "          timestamp  value\n",
      "629   1590782217000    2.0\n",
      "701   1590782277000    3.0\n",
      "719   1590782285000    3.0\n",
      "854   1590782398000    3.0\n",
      "925   1590782458000   13.0\n",
      "994   1590782517000    2.0\n",
      "1075  1590782577000    2.0\n",
      "1093  1590782585000    2.0\n",
      "1203  1590782697000    3.0\n",
      "1284  1590782757000    2.0\n",
      "1307  1590782765000    3.0\n",
      "1424  1590782879000    3.0\n",
      "1487  1590782939000    2.0\n",
      "1568  1590782999000    3.0\n",
      "1629  1590783058000    2.0\n",
      "1664  1590783065000    3.0\n",
      "1790  1590783178000    3.0\n",
      "1853  1590783237000    2.0\n",
      "1925  1590783298000    3.0\n",
      "2077  1590783439000   87.0\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "          timestamp  value\n",
      "700   1590868928000    2.0\n",
      "759   1590868968000    2.0\n",
      "817   1590869019000   37.0\n",
      "921   1590869109000    2.0\n",
      "975   1590869150000   13.0\n",
      "1085  1590869237000    2.0\n",
      "1139  1590869289000   12.0\n",
      "1184  1590869319000   20.0\n",
      "1274  1590869379000   21.0\n",
      "1355  1590869469000    2.0\n",
      "1386  1590869499000   37.0\n",
      "1512  1590869589000    2.0\n",
      "1566  1590869640000    2.0\n",
      "1620  1590869679000   11.0\n",
      "1702  1590869763000   12.0\n",
      "1711  1590869769000    4.0\n",
      "1810  1590869860000   30.0\n",
      "1882  1590869919000   45.0\n",
      "2000  1590870013000   45.0\n",
      "2062  1590870075000   50.0\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='timestamp', ylabel='value'>"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for row_index in range(len(anomalies)):\n",
    "    anomaly = anomalies.iloc[row_index,:]\n",
    "    if anomaly['fault'] == 'CPU fault':\n",
    "        rel_kpi = get_cf_kpi(anomaly)\n",
    "        print(rel_kpi[['timestamp','value']].tail(20))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "docker_003\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='timestamp', ylabel='value'>"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "all_hosts = get_host(anomaly)\n",
    "all_hosts = all_hosts[all_hosts.name == 'container_cpu_used']\n",
    "print(anomaly['host'])\n",
    "sns.lineplot(x='timestamp', y='value', hue='cmdb_id', data=all_hosts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "for host in all_hosts['cmdb_id'].unique():\n",
    "    all_hosts[all_host['']]\n",
    "all_hosts['value'] = (all_hosts['value'] - all_hosts['value'].mean())/(all_hosts['value'].std())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='timestamp', ylabel='value'>"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.lineplot(x='timestamp', y='value', hue='cmdb_id', data=all_hosts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
